Modeling Visit Potential to Predict Hotspots of a Future District

Abstract

Understanding frequentation patterns allows urban planners to optimize the allocation of resources and infrastructure development. This includes determining the locations for schools, hospitals, public transportation, parks, and other amenities to efficiently meet the needs of the population. This paper proposes a study of the Visit Potential Model, an integrated model for evaluating the characteristics of public spaces. It is used to predict the potential potential presence of people in specific locations or public places. The model combines a universal law of visit frequencies in cities with a gravity measurement of accessibility. The adapted Visit Potential Model is represented as a graph by connecting public spaces to other spaces: population objects and attractor objects. Population objects represent places where people go in and out, such as houses, offices, and schools. Attractor objects include destinations that people visit, such as leisure parks and shopping malls. Originally, this static model was defined for a single time-frame by explicitly taking into the account the time component and a dynamic model was derived. A future district under construction was used as a case study: a multimodal transportation model was built to simulate and analyze the motion of people. The reported outcomes can be analyzed to provide us first insights of the potential for visiting the district’s public spaces and define its future hotspots and places of interaction.

Keywords

• daily planning
• activity-based model
• urban planning
• city life
• infrastructure